Compressed Sensing: Underwater Acoustic Channel Estimation with Doppler Shifts

Underwater acoustic (UWA) channels are wideband in nature due to the small ratio of the carrier frequency to the signal bandwidth, which introduces frequency dependent on Doppler spread. Compressed Sensing (CS) offers a method to solve the channel estimation problems for an UWA system, based on the existence of a sparse representation of the treated signal and an over-complete dictionary with a set of non-orthogonal bases. In this paper, we propose a new type of channel estimator using the compressed sensing theory, which releases the sparse channel estimation from the highly dependence on Doppler compensation. Instead of using various compensation approaches, the proposed index is designed by modeling Doppler shifts as the atoms shifts in over-complete dictionary. From the results, this method improves the mean square error (MSE) performance with lower complexity and hardware cost. In addition, the new method has the additional benefit being less sensitive to Doppler rate variety. The simulation results show the robustness of the new channel estimator for Doppler effects.